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1.
《Journal of The Franklin Institute》2021,358(13):6508-6525
For multi-agent system (MAS), most of existing iterative learning control (ILC) algorithms consider about the tracking of reference defined over the whole trial interval, while the point-to-point (P2P) task, where the emphasis is placed on the tracking of intermediate time points, has not been explored. Thus, a distributed ILC method is proposed, in which each agent updates the feedforward control input by learning from the experience of itself and its neighbors in previous repeated tasks to achieve the goal of improving performance. In addition, for the sake of reducing the burden of data transmission in MAS, effective data quantization is essential. In this case, the quantitative measurement of the error of the tracking time points is further used in the ILC updating law. In order to accommodate this requirement, a distributed point-to-point iterative learning control (P2PILC) with tracking error quantization for MAS is first proposed in this paper. A necessary and sufficient condition is presented for the asymptotical stability of the proposed algorithm, and simulation results show the effectiveness of it finally. 相似文献
2.
《Journal of The Franklin Institute》2023,360(14):10706-10727
Distributed optimization over networked agents has emerged as an advanced paradigm to address large-scale control, optimization, and signal-processing problems. In the last few years, the distributed first-order gradient methods have witnessed significant progress and enrichment due to the simplicity of using only the first derivatives of local functions. An exact first-order algorithm is developed in this work for distributed optimization over general directed networks with only row-stochastic weighted matrices. It employs the rescaling gradient method to address unbalanced information diffusion among agents, where the weights on the received information can be arbitrarily assigned. Moreover, uncoordinated step-sizes are employed to magnify the autonomy of agents, and an error compensation term and a heavy-ball momentum are incorporated to accelerate convergency. A linear convergence rate is rigorously proven for strongly-convex objective functions with Lipschitz continuous gradients. Explicit upper bounds of step-size and momentum parameter are provided. Finally, simulations illustrate the performance of the proposed algorithm. 相似文献
3.
针对PID控制器在不同的应用系统,需要动态调整PID控制参数的问题,提出了基于遗传算法的PID自适应参数优化方案。该方案通过将PID控制器产生的误差作为目标函数,利用遗传算法实现对PID控制器参数的自动调整。为了提高参数的优化效率,文章通过对交叉算子和变异算子的自适应处理,提高了PID控制器的性能。实验测试表明,文章设计的PID参数优化策略比普通的基于遗传算法优化策略效率平均高14.7%。 相似文献
4.
This paper investigates the optimal tracking performance of the multiple-input multiple-output (MIMO) discrete-time networked control systems (NCSs) considering the quantization of communication channel. The tracking performance is adopted for the H2 square error criterion. The optimal tracking performance expression is obtained by using the co-prime factorization, the partial factorization, the inner–outer factorization and the spectral decomposition methods. Moreover, the paper also includes the exploration of the optimal tracking performance with input power constraint. The obtained results have demonstrated that the optimal tracking performance is influenced by the non-minimum phase zeros, unstable poles and their directions, the reference signal and the quantization interval. Moreover the theoretical results have also been proven using a number of different examples. 相似文献
5.
《Journal of The Franklin Institute》2019,356(12):6352-6372
In precision motion systems, well-designed feedforward control can effectively compensate for the reference-induced error. This paper aims to develop a novel data-driven iterative feedforward control approach for precision motion systems that execute varying reference tasks. The feedforward controller is parameterized with the rational basis functions, and the optimal parameters are sought to be solved through minimizing the tracking error. The key difficulty associated with the rational parametrization lies in the non-convexity of the parameter optimization problem. Hence, a new iterative parameter optimization algorithm is proposed such that the controller parameters can be optimally solved based on measured data only in each task irrespective of reference variations. Two simulation cases are presented to illustrate the enhanced performance of the proposed approach for varying tasks compared to pre-existing results. 相似文献
6.
《Journal of The Franklin Institute》2022,359(17):10172-10205
Recently, the sparsity-aware sign subband adaptive filter algorithm with individual-weighting-factors (S-IWF-SSAF) was devised. To accomplish performance enhancement, the variable parameter S-IWF-SSAF (VP-S-IWF-SSAF) algorithm was developed through optimizing the step-size and penalty factor, respectively. Different from the optimization scheme, we devise a family of variable step-size strategy S-IWF-SSAF (VSS-S-IWF-SSAF) algorithms based on the transient model of algorithms via minimizing the mean-square deviation (MSD) on each iteration with some reasonable and frequently adopted assumptions and Price's theorem. And in order to enhance the tracking capability, an effective reset mechanism is also incorporated into the proposed algorithms. It is worth mentioning that the presented algorithms could acquire lower computational requirements and exhibit higher steady-state estimation accuracy obviously and acceptable tracking characteristic in comparison to the VP-S-IWF-SSAF algorithm. In addition, the stable step-size range in the mean and mean square sense and steady-state performance are concluded. And the computational requirements are exhibited as well. Monte-Carlo simulations for system identification and adaptive echo cancellation applications certify the proposed algorithms acquire superior performance in contrast to other related algorithms within various system inputs under impulsive interference environments. 相似文献
7.
基于块奇异值分解的水印算法研究 总被引：8，自引：0，他引：8
奇异值分解是一种特殊的矩阵变换，并具有良好的性质。本文充分利用奇异值分解的特性，提出了一种新的基于块奇异值分解的量化水印算法和一种新的基于块奇异值分解的扩频水印算法。这两个算法都是通过对各个数据块的最大奇异值进行修改来嵌入水印，都可以根据待嵌入的水印信息量来调整分块的大小，算法的复杂度较低。其中的量化水印算法是含边信息的嵌入方法，可以实现盲检测。实验结果证明，基于块奇异值分解的水印算法对常规的图像处理攻击具有很好的鲁棒性，尤其是其中的量化水印算法。 相似文献
8.
This paper presents a stochastic multi-parameters divergence method for online parameter optimization of fractional-order proportional–integral–derivative (PID) controllers. The method is used for auto-tuning without the need for exact mathematical plant model and it is applicable to diverse plant transfer functions. The proposed controller tuning algorithm is capable of adaptively responding to parameter fluctuations and model uncertainties in real systems. Adaptation skill enhances controller performance for real-time applications. Simulations and experimental observations are carried on a prototype helicopter model to confirm the performance improvements obtained by the online auto-tuning of fractional-order PID structure in laboratory conditions. 相似文献
9.
《Journal of The Franklin Institute》2023,360(13):9579-9601
The current parking trajectory planning algorithms based on geometric connections or formulation of optimization problems in automatic parking systems have strict requirements on the starting position, lower planning efficiency and discontinuous curvature of the reference trajectory. In order to solve these problems, a hierarchical planning algorithm which is combined with nonlinear optimization and the improved RRT* algorithm (Rapidly-exploring Random Tree Star) with Reeds-Shepp curve is proposed in this paper. First, the improved RRT*RS algorithm with the rapid repulsion-straddle experiment is designed for enhancing the efficiency of path planning. Second, because of the shortcomings of the Reeds-Shepp curve that can meet the minimum turning radius but not realize the continuous curvature of the path, a nonlinear optimization problem based on convex-set obstacle constraints is formulated and solved. Finally, simulation results show that the proposed parking trajectory planning algorithm in this paper can plan an effective parking trajectory with continuous curvature in different starting positions and multiple parking scenarios. 相似文献
10.
率失真优化技术在视频优化编码中起着重要的作用，广泛地应用于宏块模式决策，优化量化等编码模块中。本文将率失真优化编码与码率控制结合起来进行研究，通过对率失真关系的分析，提出了基于率失真优化的复杂度可分级码率控制算法，并根据缓冲区操作模型的位分配约束条件调整码率控制的位分配过程，从而使得该算法能够在达到码率控制的同时也能取得较高的编码效率，并能保证缓冲区不会发生溢出，然后结合场景变换、图像内容分类等主观质量问题研究，提出一种恒定质量码率控制编码算法。 相似文献
11.
针对OFDM系统峰均比PAPR过大而限制其应用的缺点,对比分析了目前优化PAPR的传统PTS(部分传输序列法)算法以及优化的PTS算法的性能与计算复杂度,在此基础上提出分组优化PTS算法,在性能与计算复杂度上有良好平衡。最后对各种算法列表对比优劣,对今后的算法研究提供一定的参考价值。 相似文献
12.
《Information processing & management》2023,60(3):103301
Hashing has been an emerging topic and has recently attracted widespread attention in multi-modal similarity search applications. However, most existing approaches rely on relaxation schemes to generate binary codes, leading to large quantization errors. In addition, amounts of existing approaches embed labels into the pairwise similarity matrix, leading to expensive time and space costs and losing category information. To address these issues, we propose an Efficient Discrete Matrix factorization Hashing (EDMH). Specifically, EDMH first learns the latent subspaces for individual modality through matrix factorization strategy, which preserves the semantic structure representation information of each modality. In particular, we develop a semantic label offset embedding learning strategy, improving the stability of label embedding regression. Furthermore, we design an efficient discrete optimization scheme to generate compact binary codes discretely. Eventually, we present two efficient learning strategies EDMH-L and EDMH-S to pursue high-quality hash functions. Extensive experiments on various widely-used databases verify that the proposed algorithms produce significant performance and outperform some state-of-the-art approaches, with an average improvement of 2.50% (for Wiki), 2.66% (for MIRFlickr) and 2.25% (for NUS-WIDE) over the best available results, respectively. 相似文献
13.
Auto-structuring fuzzy neural system for intelligent control 总被引：1，自引：0，他引：1
Kuo-Hsiang Cheng 《Journal of The Franklin Institute》2009,346(3):267-288
An auto-structuring fuzzy neural network-based control system (ASFNS), which includes the auto-structuring fuzzy neural network (ASFNN) controller and the supervisory controller, is proposed in this paper. The ASFNN is used as the main controller to approximate the ideal controller and the supervisory controller is incorporated with the ASFNN for coping with the chattering phenomenon of the traditional sliding-mode control. In the ASFNS, an automatic structure learning mechanism is proposed for network structure optimization, where two criteria of node-adding and node-pruning are introduced. It enables the ASFNN to determine the nodes autonomously while ensures the control performance. In the ASFNS, all the parameters are evolved by the means of the Lyapunov theorem and back-propagation to ensure the system stability. Thus, an intelligent control approach for adaptive control is presented, where the structure and parameter can be evolved simultaneously. The proposed ASFNS features the following salient properties: (1) on-line and model-free control, (2) relax design in controller structure, (3) overall system stability. To investigate the capabilities, the ASFNS is applied to a kind of nonlinear system control. Through the simulation results the advantages of the proposed ASFNS can be validated. 相似文献
14.
提出了一种星载合成孔径雷达(SAR)回波中频采样后直接分块自适应量化(BAQ)的设计.从理论上证明了中频BAQ的可行性.与中频回波数字下变频后再BAQ的典型结构相比,该设计将数字下变频放到地面进行,简化了电路结构,节省了硬件资源.采用免混频结构时,仿真结果表明:下传数据率相同的情况下两者的性能接近,新方案所耗费的硬件资源不到前者的1/3. 相似文献
15.
In recent years, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Ease of use, broad applicability, and global perspective may be considered as the primary reason for their success. The honey-bee mating process has been considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bee mating. In this paper, the honey-bee mating optimization (HBMO) algorithm is presented and tested with a nonlinear, continuous constrained problem with continuous decision and state variables to demonstrate the efficiency of the algorithm in handling the single reservoir operation optimization problems. It is shown that the performance of the model is quite comparable with the results of the well-developed traditional linear programming (LP) solvers such as LINGO 8.0. Results obtained are quite promising and compare well with the final results of the other approach. 相似文献
16.
A self-organization algorithm for image compression and the associated VLSI architecture are presented. A frequency upper-threshold is effectively used in the centroid learning method. Performances of the self-organization networks and traditional nonself-organization algorithms for vector quantization are compared. This new algorithm is quite efficient and can achieve near-optimal results. A trainable VLSI neuroprocessor based upon this new self-organization network has been developed for high-speed and high-ratio image compression applications. This neural-based vector quantization design includes a fully parallel vector quantizer and a pipelined codebook generator which obtains a time complexity O (1) for each quantization vector. A 5 × 5-dimensional vector quantizer prototype chip has been designed and fabricated. It contains 64 inner-product neural units and an extendable winner-take-all block. This mixed-signal chip occupies a compact silicon area of 4.6 × 6.8 mm2 in a 2.0-μm scalable CMOS technology. It provides a computing capability as high as 3.33 billion connections per second. It can achieve a speedup factor of 110 compared with a SUN-4/75 workstation for a compression ratio of 33. Real-time adaptive VQ on industrial 1024 × 1024 pixel images is feasible using multiple neuroprocessor chips. An industrial-level design to achieve 104 billion connections per second for the 1024-codevector vector quantizer can be fabricated in a 125 mm2 chip through a 1 μm CMOS technology. 相似文献
17.
Junhong Li Wei Xing Zheng Juping Gu Liang Hua 《Journal of The Franklin Institute》2017,354(1):316-331
This paper studies the parameter estimation problem of Hammerstein output error autoregressive (OEAR) systems. According to the maximum likelihood principle and the Levenberg–Marquardt optimization method, a maximum likelihood Levenberg–Marquardt recursive (ML-LM-R) algorithm using the varying interval input–output data is proposed. Furthermore, a stochastic gradient algorithm is also derived in order to compare it with the proposed ML-LM-R algorithm. Two numerical examples are provided to verify the effectiveness of the proposed algorithms. 相似文献
18.
Vera Luki&#x; Svetlana Ignjatovi&#x; 《Biochemia medica : ?asopis Hrvatskoga dru?tva medicinskih biokemi?ara / HDMB》2022,32(1)
IntroductionMoving average (MA) is one possible way to use patient results for analytical quality control in medical laboratories. The aims of this study were to: (1) implement previously optimized MA procedures for 10 clinical chemistry analytes into the laboratory information system (LIS); (2) monitor their performance as a real-time quality control tool, and (3) define an algorithm for MA alarm management in a small-volume laboratory to suit the specific laboratory.Materials and methodsMoving average alarms were monitored and analysed over a period of 6 months on all patient results (total of 73,059) obtained for 10 clinical chemistry parameters. The optimal MA procedures were selected previously using an already described technique called the bias detection simulation method, considering the ability of bias detection the size of total allowable error as the key parameter for optimization.ResultsDuring 6 months, 17 MA alarms were registered, which is 0.023% of the total number of generated MA values. In 65% of cases, their cause was of pre-analytical origin, in 12% of analytical origin, and in 23% the cause was not found. The highest alarm rate was determined on sodium (0.10%), and the lowest on calcium and chloride.ConclusionsThis paper showed that even in a small-volume laboratory, previously optimized MA procedures could be successfully implemented in the LIS and used for continuous quality control. Review of patient results, re-analysis of samples from the stable period, analysis of internal quality control samples and assessment of the analyser malfunctions and maintenance log have been proposed for the algorithm for managing MA alarms. 相似文献
19.
《Information processing & management》2023,60(2):103205
Personalized recommender systems have been extensively studied in human-centered intelligent systems. Existing recommendation techniques have achieved comparable performance in predictive accuracy; however, the trade-off between recommendation accuracy and diversity poses new challenges, as diversification may lead to accuracy loss, whereas it can solve the over-fitting problem and enhance the user experience. In this study, we propose a heuristic optimization-based recommendation model that jointly optimizes accuracy and diversity performance by obtaining a set of optimized solutions. To establish the best accuracy-diversity balance, a novel trajectory-reinforcement-based bacterial colony optimization algorithm was developed. The improved bacterial colony optimization algorithm was comprehensively evaluated by comparing it with eight popular and state-of-the-art algorithms on ten benchmark testing problems with different degrees of complexity. Furthermore, an optimization-based recommendation model was applied to a real-world recommendation dataset. The results demonstrate that the improved bacterial colony optimization algorithm achieves the best overall performance for benchmark problems in terms of convergence and diversity. In the real-world recommendation task, the proposed approach improved the diversity performance by 1.62% to 8.62% while maintaining superior (1.88% to 40.32%) accuracy performance. Additionally, the proposed personalized recommendation model can provide a set of nondominated solutions instead of a single solution to accommodate the ever-changing preferences of users and service providers. Therefore, this work demonstrates the excellence of an optimization-based recommendation approach for solving the accuracy-diversity trade-off. 相似文献